Fault Classification with Convolutional Neural Networks for Microgrid Systems

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Process</td><td class="align_center">Preprocessing with DWT</td><td class="align_center">Image generation</td><td class="align_center">Model training</td><td class="align_center">Fault classification</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Average Time</td><td class="align_center"><span style="width: 33.8006ptpx;"><svg height="8.55521pt" id="M348" style="vertical-align:-0.2063904pt" version="1.1" viewbox="-0.0498162 -8.34882 33.8006 8.55521" width="33.8006pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"></path></g><g transform="matrix(.013,0,0,-0.013,6.24,0)"><path d="M113 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<div>Average training and testing time for fault classifier development.</div>

International Transactions on Electrical Energy Systems

tab7

Table 7

Table 7: Fault Classification with Convolutional Neural Networks for Microgrid Systems 